cali0123
/

pronunciation_accuracy

Audio Classification

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pronunciation_accuracy

This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9277
Accuracy: 0.623

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	125	0.8216	0.639
No log	2.0	250	0.8341	0.638
No log	3.0	375	0.9277	0.623

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Downloads last month: 0

Safetensors

Model size

20.7M params

Tensor type

F32

·

Inference Examples

Audio Classification

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Model tree for cali0123/pronunciation_accuracy

Base model

openai/whisper-base

Finetuned

(335)

this model

Evaluation results

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